Search

Selecting appropriate mapping units is vital for landslide susceptibility mapping as well as pattern investigation, given that various units-based analyses extensively control the prediction performances. This paper investigated the landslide development through the interpretation and field surveys along the Yunling–Yanjing segment of the Lancang River in southeastern Tibet, and fulfil LSM with the consideration of 15 conditioning factors. Two grid unit methods (single-point and multi-point patterns) and two slope unit methods were comparatively analyzed for model training and mapping of landslide susceptibility via machine learning algorithms. The results suggest that the landslides are preferentially distributed in an elevation range of 2000–4000 m, in a slope range of 20–40°, a local relief range of 1000–2500 m, and southwest-oriented slopes. The data extracted by the multi-point method denotes a higher representation of landslide development features. All models possessed positive prediction ability for landslide susceptibility, and the multi-point method based on grid unit performed the best with the AUC exceeding 0.9. The best-performing models indicated that zones of high and very high susceptibility mainly distributed adjacent to the mainstem and some tributaries of the Lancang River. Furthermore, the distribution of "safety islands" (the slopes less prone to landslides) along National Highway G214 was reasonably illustrated as well, which provides a hazard predictability for such an important transportation corridor along the deeply-incised valley in the Lancang River. This study demonstrates a theoretical basis for the regional disaster prevention and mitigation for human activity, and provides methodological references for landslide susceptibility evaluation in similar mountainous areas over the world. [ABSTRACT FROM AUTHOR]

Among natural hazards occurring offshore, submarine landslides pose a significant risk to offshore infrastructure installations attached to the seafloor. With the offshore being important for current and future energy production, there is a need to anticipate where future landslide events are likely to occur to support planning and development projects. Using the northern Gulf of Mexico (GoM) as a case study, this paper performs Landslide Susceptibility Mapping (LSM) using a gradient-boosted decision tree (GBDT) model to characterize the spatial patterns of submarine landslide probability over the United States Exclusive Economic Zone (EEZ) where water depths are greater than 120 m. With known spatial extents of historic submarine landslides and a Geographic Information System (GIS) database of known topographical, geomorphological, geological, and geochemical factors, the resulting model was capable of accurately forecasting potential locations of sediment instability. Results of a permutation modelling approach indicated that LSM accuracy is sensitive to the number of unique training locations with model accuracy becoming more stable as the number of training regions was increased. The influence that each input feature had on predicting landslide susceptibility was evaluated using the SHapely Additive exPlanations (SHAP) feature attribution method. Areas of high and very high susceptibility were associated with steep terrain including salt basins and escarpments. This case study serves as an initial assessment of the machine learning (ML) capabilities for producing accurate submarine landslide susceptibility maps given the current state of available natural hazard-related datasets and conveys both successes and limitations. [ABSTRACT FROM AUTHOR]

Landslide monitoring is a mandatory step in landslide risk assessment. It requires collecting data on landslide conditions (e.g., areal extent, landslide kinematics, surface topography, hydrogeometeorological parameters, and failure surfaces) from different time periods and at different scales, from site-specific to local, regional, and national, to assess landslide activity. In this analysis, we collected information on landslide monitoring techniques from 17 members of the Earth Observation and Geohazards Expert Group (from EuroGeoSurveys) deployed between 2005 and 2021. We examined the types of the 75 recorded landslides, the landslide techniques, spatial resolution, temporal resolution, status of the technique (operational, non-operational), time of using (before the event, during the event, after the event), and the applicability of the technique in early warning systems. The research does not indicate the accuracy of each technique but, rather, the extent to which Geological Surveys conduct landslide monitoring and the predominant techniques used. Among the types of landslides, earth slides predominate and are mostly monitored by geological and engineering geological mapping. The results showed that Geological Surveys mostly utilized more traditional monitoring techniques since they have a broad mandate to collect geological data. In addition, this paper provides new insights into the role of the Geological Surveys on landslide monitoring in Europe and contributes to landslide risk reduction initiatives and commitments (e.g., the Kyoto Landslide Commitment 2020). [ABSTRACT FROM AUTHOR]

The great M ~ 8 1920 Haiyuan earthquake (HYEQ) was one of the largest and most deadly earthquakes in China in the last century, with ~ 234,000 deaths. The earthquake occurred within the Loess Plateau of northern China, where Quaternary loess deposits form a distinctive blanket across the landscape. Large regions of this loess cover experienced co-seismic landslides. Based on an analysis of the original disaster reports, field surveys, and satellite image interpretation, we have compiled the shaking effects of the earthquake, including the distribution of landslides, fatalities, and structural damage. Landslides triggered by the HYEQ (n > 7,000) are concentrated south of the Haiyuan fault, in a region that has both thick loess cover and long-term relief generated by the drainage network. This distribution is spatially separated from landslides triggered by other earthquakes. We find that in contrast to previous studies, the most important factor in the severe death toll of the HYEQ was the collapse of housing by ground shaking, including collapse of loess house-caves. Landslides were a secondary factor; although up to 32,000 deaths occurred in areas with intense landsliding. Based on the revised distribution pattern of landslides and damage (e.g., house collapses), we suggest that the isoseismal intensity IX line extends south of previous locations. We have also identified 126 dammed lakes created by co-seismic landslides, which form major modifications of this semi-arid landscape. The research methods in this paper, combining historical review, satellite image interpretation, and field validation of landslides, can be used as a reference for studies of other areas affected by historical earthquakes and co-seismic landslides, elsewhere in the Loess Plateau and beyond. [ABSTRACT FROM AUTHOR]

Most previous studies on the quantitative risk assessment (QRA) of landslides focused on the probability of slope failure at the pre-failure stage and adopted empirical models for consequence analysis. The conventional approaches simplify the relationship between the pre-failure state and the post-failure behavior and cannot reasonably account for the effects of uncertainty on the entire landslide process. In this paper, an efficient QRA method that involves the direct simulation of the entire landslide process is proposed. A QRA formula that considers the probability of only those landslides that can impact the element at risk is used. The coupled Eulerian–Lagrangian method is used to simulate the entire landslide process and to identify slopes that can impact the element at risk and determine the failure consequences. The subset simulation method is adopted to efficiently estimate the probability of landslide impact, and parameter uncertainty is considered. Two case histories of landslides are investigated. First, the 2011 Baqiao loess landslide in Xi'an, China, is investigated, and the results of the proposed method are compared with those of the conventional approaches. Second, the proposed method is applied to assess the risk of the 2015 Ganjingzi landslide in the Three Gorges Reservoir. The effects of the risk mitigation works are also discussed. [ABSTRACT FROM AUTHOR]

In this paper, the artificial bee colony (ABC) algorithm is used to generate landslide susceptibility maps. To the best of our knowledge, it is the first time the ABC algorithm is applied as a classifier on landslide susceptibility mapping. Twelve features are considered as inputs for the ABC model in this research work. These features contain redundant and correlated information. Therefore, normalization and dimension reduction are applied in the pre-processing stage. Three different normalization methods are investigated, i.e. minimum and maximum (Min-Max), mean standard deviation (Mean-SD), and median and interquartile range (Med-IQR). Two dimensionality reduction techniques, i.e., principal component analysis (PCA) and canonical variate analysis (CVA), are utilized to deal with high-dimensional information and eliminate correlated information in the data. In total, six different schemes of input data based on the three normalization methods and two techniques of dimension reduction are applied to train the ABC model. There are a total of 382 landslide incidents occurred at various locations on Penang Island, out of which 255 are selected for training and remaining 127 are used for the validation purpose of the model. The model classification accuracies and receiver of characteristics (ROC) curve are applied to evaluate the model's performance. The results show that the ABC model trained using Min-Max normalization and CVA scheme generates the best results among these six schemes. The landslide susceptibility maps generated in this research offer significant information for landslide risk management. [ABSTRACT FROM AUTHOR]

Long-runout landslides can be extremely hazardous and unpredictable. The prediction of long-runout landslides is challenging because it is unclear what factors control their mobility, and it is unclear how to best measure their runout given that they traverse changing topography. In this paper, we document the development and statistical evaluation of a Landslide Runout Score (LRS) system to predict short, medium, and long runout using a new mobility measure, the unitless Runout Number L/A1/2 (where L is landslide length and A is landslide area). The Runout Number has previously been correlated to three geomorphological factors (planimetric curvature, sand content, and upslope contributing area normalized to landslide area), so the LRS uses these factors as inputs. These factors are readily calculated using geographic information systems (GIS) and publicly available data sources. The LRS system predicts runout categories (short, medium, and long) with one-vs.-all accuracies (i.e., percentage of correct predictions within a given class) of 75, 58, and 72%, respectively, for a total weighted accuracy of approximately 65%. The results of this work are summarized in a worksheet that can be used by geologists and engineers to develop preliminary predictions of landslide runout behavior, which can be incorporated into or used alongside regional-scale landslide hazard assessments. [ABSTRACT FROM AUTHOR]

Chalk exposures in coastal cliff faces extend from Yorkshire to Devon in England and from Boulonnais to Normandy in France. The failure of chalk cliffs is a long-recognised hazard along parts of these coastlines; however, variation in the chalk's lithology, stratigraphy and physical properties coupled with changing topographic relief, means that the nature of the hazard is variable. This paper is concerned with cliff failures that may lead to chalk flow resulting in catastrophic flow slide or sturzstrom-like behaviour. The paper discusses the nature of chalk flows and how they relate to other types of flow-like sturzstroms. Recently published and unpublished work is used to unify simple mechanical index properties between the French and English coastal chalks. Some well-documented studies are then re-examined, using these results and in the light of new findings on sturzstroms to show how runout is controlled by chalk porosity. Finally, a series of physical model tests are described in which some of the controls on runout of the chalk are examined. [ABSTRACT FROM AUTHOR]

Rapid detection of landslides using remote sensing images plays a key role in hazard assessment and mitigation. Many deep convolutional neural network-based models have been proposed for this purpose; however, for small-scale landslide detection, excessive convolution and pooling process may cause potential texture information loss, which can lead to misclassification of landslide target. In this paper, we present a novel UNet model for the automatic detection of landslides, wherein the reversed image pyramid features (RIPFs) are adapted to mitigate the information loss caused by a succession of convolution and pooling. The proposed RIPF-Unet model is trained and validated using the open-source landslides dataset of the Bijie area, Guizhou Province, China, wherein the precision of the proposed model is observed to increase by 3.5% and 4.0%, compared to the conventional UNet and UNet + + model, respectively. The proposed RIPF-Unet model is further applied to the case of the Longtoushan region after the 2014 Ms.6.5 Ludian earthquake. Results show that the proposed model achieves a 96.63% accuracy for detecting landslides using remote sensing images. And the RIPF-Unet model is also advanced in its compact parameter size; notably, it is 31% lighter compared to the UNet + + model. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to compare and evaluate the performance of two multicriteria models for landslide susceptibility assessment in Constantine, north-east of Algeria. The landslide susceptibility maps were produced using the analytic hierarchy process (AHP) and Fuzzy AHP (FAHP) via twelve landslides conditioning factors, including the slope gradient, lithology, land cover, distance from drainage network, distance from the roads, distance from faults, topographic wetness index, stream power index, slope curvature, Normalized Difference Vegetation Index, slope aspect and elevation. In this study, the mentioned models were used to derive the weighting value of the conditioning factors. For the validation process of these models, the receiver operating characteristic analysis, and the area under the curve (AUC) were applied by comparing the obtained results to The landslide inventory map which prepared using the archives of scientific publications, reports of local authorities, and field survey as well as analyzing satellite imagery. According to the AUC values, the FAHP model had the highest value (0.908) followed by the AHP model (0.777). As a result, the FAHP model is more consistent and accurate than the AHP in this case study. The outcome of this paper may be useful for landslide susceptibility assessment and land use management. [ABSTRACT FROM AUTHOR]

Landslides are common occurrences along Chinese rail routes. Accordingly, the accurate determination of sliding-surface locations and the underlying causes become critical from the landslide-disaster-management and loss-mitigation viewpoints. In this study, the landslide in the K66 section of the Jiheng Railway (installed in Jinggangshan City, Jiangxi, China) was investigated. The causative factors and characteristics of the landslide were analyzed using geophysical methods as well as drilling and monitoring techniques. The results reveal that a combination of the transient electromagnetic method and electrical resistivity tomography can be used to identify the location of water-rich landslide-prone regions. When combined with the drilling information, these results reveal the tendency of landslide occurrence in regions comprising strongly weathered carbonaceous shale. Moreover, an uneven slope deformation is observed along the railway line. The seepage of surface water into the slope is revealed as the primary cause of landslides. This is because the reduced strength of the strongly weathered carbonaceous shale facilitates the formation of sliding surfaces. This paper presents a comprehensive survey plan for landslides occurring along railway routes. Furthermore, an assessment of the risk of future landslide occurrences in the investigation area is presented, thereby providing an appropriate reference for landslide prevention and loss mitigation. [ABSTRACT FROM AUTHOR]

Landslide is a uniquely dynamic large-deformation process that can present serious threat to human lives and infrastructures. The natural soil properties often exhibit inherent spatial variability, which affects the landslide behavior significantly. This paper focuses on combined Monte Carlo simulation and three-dimensional (3D) dynamic large-deformation finite-element (LDFE) analysis using the coupled Eulerian-Lagrangian method to investigate the whole runout process of landslide induced by the earthquake in spatially varying soil. The results from LDFE analysis show that the mean value of runout distance in spatially varying soil is significantly higher than that of the deterministic value obtained from a homogeneous slope due to the slope failure developed along the weakest path in soils. The mean runout distance increases and converges with increasing slope length in 3D-LDFE stochastic analysis. The advantages and necessities of 3D-LDFE analysis were illustrated by comparing it with two-dimensional (2D) LDFE analysis of landslide in spatially varying soil. The results show that the calculated mean runout distance using 3D-LDFE method is at least 16.1% higher than that calculated using 2D-LDFE analysis. Finally, a linear regression formula was established to estimate the mean runout distance of landslide due to horizontal inertia acceleration. Such a formula may facilitate the risk assessment of landslide in practical engineering. [ABSTRACT FROM AUTHOR]

An integrated investigation of possible factors responsible for reoccurring landslide at Agbona Hill of Okemesi, in a typical Basement Complex terrain of southwestern Nigeria is presented in this paper. The landslide which rises to about 18.62 m at the point of failure, strikes N-S direction, and measured about 8.54 m in width and extends down the slope in length of about 265 m. The landslide which occurred immediately to the north of residential area resulted into damages of buildings and the road along the path of the mass movement. The investigation which involved resistivity imaging along four traverses with length varying between 180 and 210 m in the N-S direction was complemented with eight vertical electrical soundings and geotechnical analysis of soils samples at ten selected points. The inferred lithological depth sections from electrical properties revealed the nature of both the upper and lower sections of the landslide with thin topsoil, having resistivity and thickness values ranging from 104 to 871 Ω-m and 0.8–1.5 m, respectively, observed to be characterized by loose sand to clayey sand and quartzite rubbles. The internal structures also revealed underlying layer classified into fairly to poorly weathered bedrock or indurated quartzite rocks. The resistivity ranges from 297 to 4381 Ω-m and the thicknesses varying from 1.3 to 9.9 m. Both sections exhibited intermediate to steep internal slope with a series of fracturing observed over the outcropped quartzite ridge that extends deeply into these layers. The fractures serve as conduit for the groundwater to flow to the surface, thereby accelerating the weathering of the rock. The results of geotechnical study showed that the upper segment of the landslide comprise of highly weathered materials characterised by sandy clay or silt materials with plasticity index of the fines indicating slight medium plasticity, thereby serving as a trigger to the landslide under prolonged and torrential rainfall arising from the movement in the soils by the flow of groundwater which seeps to the surface through the fractures in the rock mass. [ABSTRACT FROM AUTHOR]

Unsaturated shallow soil deposits may be affected by either superficial soil erosion or shallow landslides in adjacent or overlapping source areas and in different seasons when a different soil suction exists. The triggering analysis of both these processes is a relevant issue for the hazard analysis while the literature mostly provides specific approaches for erosion or for landslides. The paper proposes a large-area analysis for a case study of Southern Italy, consisting of unsaturated shallow deposits of loose pyroclastic (air-fall) volcanic soils that have been repeatedly affected by erosion and landslides in special seasons. For a past catastrophic event, the simulated source areas of shallow landslides are smaller than those observed in the field while the simulated eroded areas with thickness greater than 5 cm are comparable with the in-situ evidences, if the analysis takes into account high rainfall intensity and a spatially variable soil cover use. More in general, the results of the paper are consistent with the previous literature and also provide a methodological contribution about the application of distinct tools over large area. The added value is that the paper shows how the combination of distinct large-area analyses may help with understanding the dominant slope instability mechanisms. Only once this goal is fully achieved, can specific physically-based analyses be confidently performed at detailed scales and for smaller specific areas. [ABSTRACT FROM AUTHOR]

Rainfall-induced landslide masses often change into disastrous debris flows and damage large areas in Nepal's mountainous region. The area covered by debris flow inundation or debris flow runout is a most essential component for landslide hazard assessments leading to development of land use plans. However, there is presently no tool that can allow to assess and predict debris flow runout from the initial landslide on the watershed scale in Nepal. In this paper, a method and simulation tool are developed for the assessment and prediction of debris flow runout in Kulekhani Watershed, Nepal. The Flow-R model with user-defined landslide-susceptible areas was chosen for debris flow runout analysis. The Flow-R model with various algorithms has the capability to analyze debris flow inundation with limited input information. Two recent debris flow events are taken as case studies to identify the appropriate algorithms for runout analysis of the study area. After comparison of the observed and simulated results for debris flow runout, the algorithms proposed by Holmgren (Hydrol Process 8:327–334, 1994) (modified) are found suitable for the study watershed. These algorithms are employed for debris flow inundation analysis in the study area with pre-defined landslide sources plus debris flow inundation map in GIS environment. The results obtained from this modeling for the debris flow area induced by 540 mm of rainfall in 24 h period was 2.68% of the watershed, which is comparable to previously observed debris flow area in the study watershed. The findings of this research and GIS simulation tool developed will enable the optimization of planning and investment for land development in the studied region. [ABSTRACT FROM AUTHOR]

Giant landslides can cause significant damage to their dynamic runout processes. Understanding the mechanics of the runout process is essential for landslide risk assessment and mitigation design. This paper investigates the runout process of the 1.16 × 109 m3 giant Daguangbao landslide triggered by the 2008 Ms 8.0 Wenchuan earthquake. The Daguangbao landslide is a typical bedding-plane slide and the properties of basal sliding surface play a key role in the runout behaviors of the landslide. The material point method (MPM) is adopted as a numerical tool of the simulations. A thermal-based velocity-weakening friction law is used to simulate the contact between the sliding body and the basal sliding surface. A strain-softening constitutive model is used to evaluate the damages inside the landslide body and their effects on the runout behaviors of the landslide. Numerical results reveal that landslide mass slides along the bedding-plane as a whole body initially and then disintegrates during the runout process. The calculated duration of sliding is 64 s and the maximum velocity reaches 60 m/s. The friction coefficient of the slip surface decreases sharply as the landslide body starts to move, and a steady-state friction coefficient μ ≈ 0.06 is reached when the velocity exceeds approximately 20 m/s. Friction degradation of the slip surface shows a sensible influence on the final runout distance and the depth of the deposit zone. The dynamic fragmentation of the landslide body, the final runout distance, and deposition topography are also significantly affected by material softening. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to continuously monitor very slow-moving translational landslides in mountainous terrain using conventional and experimental differential global navigation satellite system (d-GNSS) technologies. A key research question addressed is whether displacement trends captured by a radio-frequency "mobile" d-GNSS network compare with the spatial and temporal patterns in activity indicated by satellite interferometric synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) photogrammetry. Field testing undertaken at Ripley Landslide, near Ashcroft in south-central British Columbia, Canada, demonstrates the applicability of new geospatial technologies to monitoring ground control points (GCPs) and railway infrastructure on a landslide with small and slow annual displacements (<10 cm/yr). Each technique records increased landslide activity and ground displacement in late winter and early spring. During this interval, river and groundwater levels are at their lowest levels, while ground saturation rapidly increases in response to the thawing of surficial earth materials, and the infiltration of snowmelt and runoff occurs by way of deep-penetrating tension cracks at the head scarp and across the main slide body. Research over the last decade provides vital information for government agencies, national railway companies, and other stakeholders to understand geohazard risk, predict landslide movement, improve the safety, security, and resilience of Canada's transportation infrastructure; and reduce risks to the economy, environment, natural resources, and public safety. [ABSTRACT FROM AUTHOR]

This paper focuses on the evaluation of temporal and spatial propagations of impulse waves using 3D numerical simulation-based models for a potential landslide area in the Tersun Dam reservoir, Northeast Turkey. The topographical model was created using Stereo Lithography files, and a drift-flux model was used to simulate the landslides. The wave generation was simulated using the Reynolds-averaged Navier–Stokes equations. The Drift-Flux approach was selected, and a renormalization group-based k-ε turbulence model was used to create a fluid–solid coupled model. The results show that a 16.5-m impulse wave is created as a result of sliding material hitting the water at a velocity of 16.4 m/s. The wave will reach the opposite shore in 27.4 s, and the run-up height will reach up to 48.8 m. As the wave, with an average velocity of 11.6 m/s in the reservoir, propagates toward the dam body, its height will decrease, and a 3.7-m-high wave will hit the dam in 155 s. A validation analysis performed using empirical equations and laboratory model tests indicates small differences in the results. The main reason for these differences is that the evaluation of wave properties is independent of the type of mass movement in empirical methods. A proper stability analysis is required to have a better estimation of the volume and the velocity of the sliding mass. [ABSTRACT FROM AUTHOR]

In a strong earthquake, not only a large number of coseismic landslides are triggered, but relaxation and cracks in the rocks and soils are induced, which make these rocks and soils vulnerable to instability during subsequent rainfall; thus, strong earthquakes always have long-term effects on landslides. The geo-hazards along the Zhaotong-Qiaojia road in the 2014 Ludian earthquake (Ms 6.5) of Yunnan Province, China, were investigated, and the Ganjiazhai giant landslide was chosen as a case study. First, using the limit equilibrium analysis and Newmark method, the critical seismic intensity of the landslide before the earthquake was evaluated. Secondly, the dynamic failure process of the landslide under the measured ground motion was simulated with the discontinuous deformation analysis method. Lastly, based on stress–seepage coupling analysis and precipitation data from Ludian meteorological station, the stability of the landslide during subsequent rainfall after the earthquake was predicted. The results show that the critical seismic intensity was within degrees VIII–IX, which is consistent with the results of the earthquake damage investigation. The dynamic failure process can be divided into four stages, and four scarps formed; the potential sliding zones during the subsequent rainfall were at the first scarp and the fourth scarp, and their critical rainfall amounts were 35–40 mm and 55–60 mm, respectively. In this paper, failure process simulation and stability prediction of the landslide before, during, and after the strong earthquake are presented, which provide analysis methods for the dynamic stability of landslides in the meizoseismal area. [ABSTRACT FROM AUTHOR]

The Loess Plateau of China is the most concentrated and largest loess area on Earth. Shanxi Province lies in the eastern margin of the Loess Plateau and is one of the regions with the worst serious soil erosion and most fragile ecological environment in the world. On March 15, 2019, a landslide hit Xiangning County in Shanxi Province in northern China and resulted in heavy casualties. This paper mainly gives an introduction about the catastrophe, causes, and related emergency response. [ABSTRACT FROM AUTHOR]

A large catastrophic landslide occurred on July 23, 2019, after a continuous heavy rainfall at Jichang (N 26°15′22.99″, E 104°40′6.33″), Shuicheng county, Guizhou province, China. This landslide had a maximum runout distance of 1295 m, a maximum falling height of 477 m between the highest point of the source area and the leading edge, and a maximum speed of 45.5 m/s. The 1.4 million cubic meters of debris instantly buried twenty-one buildings, destroyed six buildings, and resulted in 42 fatalities and 9 people missing. This paper analyzes the extent and mechanisms of initiation and runout distance of the landslide. The landslide occurred in the eluvial and deluvial accumulation of basalt, and its initiation mechanisms were different from the bedrock landslides that are typical of the interbedded soft and hard rocks in Guizhou and basalt landslides in Southwest China. The prolonged heavy rainfall, lush vegetation, and road construction played the roles in landslide initiation. Subsequently, the landslide can be divided into three sliding regions caused by the valley on both sides and the stepped terrain in the middle, and the valley topography enhanced the disaster intensity and reach. [ABSTRACT FROM AUTHOR]

Rainfall-triggered landslides have posed significant threats to human lives and property each year in China. This paper proposed a meteorological-geotechnical early warning system GRAPES-LFM (GRAPES: Global and Regional Assimilation and PrEdiction System; LFM: Landslide Forecast Model), basing on the GRAPES model and the landslide predicting model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-Stability Model) for predicting rainfall-triggered landslides. This integrated system is evaluated in Dehua County, Fujian Province, where typhoon Bilis triggered widespread landslides in July 2006. The GRAPES model runs in 5 km×5 km horizontal resolution, and the initial fields and lateral boundaries are provided by NCEP (National Centers for Environmental Prediction) FNL (Final) Operational Global Analysis data. Quantitative precipitation forecasting products of the GRAPES model are downscaled to 25 m×25 m horizontal resolution by bilinear interpolation to drive the TRIGRS model. Results show that the observed areas locate in the high risk areas, and the GRAPES-LFM model could capture about 74% of the historical landslides with the rainfall intense 30mm/h. Meanwhile, this paper illustrates the relationship between the factor of safety (FS) and different rainfall patterns. GRAPES-LFM model enables us to further develop a regional, early warning dynamic prediction tool of rainfall-induced landslides. [ABSTRACT FROM AUTHOR]

On February 05 2016, a significant and unfortunate series of mine disasters occurred at the Lily gold mine in South Africa, where 79 mineworkers were trapped under a huge rock and soil mass. In this paper, two separate geographical information system based models are proposed; one for surface and one for subsurface mine disasters. The multi-temporal (2004–2017) high-resolution pre and post-disaster satellite images were analyzed to assess the magnitude and spatial extent of the surface disaster. The explicit modeling technique was applied for mine subsidence using the Mohr–Coulomb failure criterion under gravitational acceleration. For surface disaster, the weighted overlay model was applied by assigning weights to hydrological (rainfall, flow direction, accumulation, and density); geological (geology and lineaments) and geomorphological (slope, aspect, and curvature) causative factors. The mine subsidence modeling results showed a subsidence zone of 55 × 24 × 71 m due to a failure of a crown pillar, whereas, in reality, it was 60 × 30 × 80 m. The deformation results showed that the lamp room wherein the miners were trapped could have been displaced somewhere at or below level 5 but above level 6 towards the southwest direction. The output of surface disaster modeling was also satisfactory and reliable as the actual two slope failures, i.e. the western and southern landslides of the Lily gold mine, located in extreme risk zones as predicted by the model. The results of this study can be useful for future mine planning and the environmental improvements at the Lily gold mine. [ABSTRACT FROM AUTHOR]

One of the important issues in identifying susceptible landslide locations is to select effective factors in the landslide of studied areas. The complexity of this issue is due to the fact that each of the factors is a part of the desired criteria, and the selection among them is a multi-criteria decision-making problem, requiring a structured and systematic approach. In the study area, the presence of large outcrops, as well as relatively thick soils formed on the formations, has caused a significant level of the province to potentially have the conditions for the movement of the tides. In addition, the situation is exacerbated by inappropriate use of natural resources, and construction of numerous rural and forest roads. In this paper, multi-criteria decision-making (MCDM) such as the fuzzy analytical hierarchy process (FAHP) and Dempster–Shafer (DeS) method was used to detect susceptible landslide locations, and output maps were verified applying the prediction–area (P–A) method for landslide purposes. The study has utilized P–A plot to evaluate and compare the obtained results of FAHP and DeS methods. The results indicated that the normalized density value achieved from P–A plots was significantly higher for the FAHP than the corresponding value for the DeS. In other words, FAHP, compared to DeS, resulted in the successful detection of landslide occurrences and more accurate classification of the study area. [ABSTRACT FROM AUTHOR]

Landslide Hazard Zonation (LSH) maps play a key role in landuse planning particularly in landslide prone areas. LSH mapping is globally accepted one for analyzing the area for landslide susceptibility. Different approaches were followed by many researchers in India to prepare landslide hazard zonation mapping depending upon their need and requirement. The Nilgiris district in Western Ghats of India is one of the severe to high landslide hazard prone areas of India. Many agencies have carried out research on LSH mapping for the Nilgiris district with different scales. A systematic study of inventory and zonation was 122carried out in 1980's by government agencies. However there is no proper updation or documentation on landslides after 1980's in the district The purpose of this paper is to review the existing landslide-related studies in the district of The Nilgiris and review the district's existing landslide hazard map with updated information. Landslide hazard maps in The Nilgiris were compiled in the GIS platform from various authenticated sources. Data on landslides from 1824 to 2014 were collected and a spatial database on landslides was created. A detailed inventory was analyzed and used for revision of the district's landslide hazard impact on the 2009 landslides.. Based on the landslide inventory and densely populated areas and repeated landslides at the same locations, the most landslide hazard areas were identified. [ABSTRACT FROM AUTHOR]

Slope instability phenomena such as mudslides represent a major geohazard in Brazil, which has caused devastation in many states and affected the lives of people, particularly in self-built settlements on steep slopes. This paper presents and discusses slope stability issues encountered in Caxias do Sul in the State of Rio Grande do Sul, which exemplifies the existing situation of landslide risk assessment in southern Brazil. Local geology and ground conditions of the area in relation to slope instability were reviewed and gaps in information required for mitigating risk were identified, such as inadequate geotechnical information and lack of full inspection and continuous monitoring of active landslides. Although risk assessment has been developed for the city and regarded as a fundamental management tool in the mitigation of landslide hazards, the study showed that the risk assessment works are outdated and not effectively considered for the development of the city. With significant unplanned urban expansion (where houses have been self-built on very steep terrains without geotechnical assessment of the ground and slope conditions), new geohazard mapping is essentially required. Several key recommendations were provided for mitigating the destructive effect of landslides and improving their management in mountainous urban settings. [ABSTRACT FROM AUTHOR]

Landslide is a disaster which may cause huge losses of human life and block the traffic on hilly area. In this paper, we present a new physically based model to simulate the dynamic flow of landslides, under a modified MPM (material point method) framework. To realistically simulate the characteristics of fracture and flow of soil medium in landslide, we introduce the modified Cambridge clay model (MCCM) from soil dynamics into the yield surface criterion to model the dynamic process of landslides. The interaction between soil and rock in the landslide is simulated by a level-set-based two-way fluid–solid coupling algorithm. Meanwhile, we propose a GPU-based optimization to calculate the signed distance function in level set to improve the efficiency of collision detection. We also simplify the hardening and softening parameter calculation algorithm of MCCM to reduce the calculation involved in landslide simulation. By choosing different values of the material yield surface parameters, various kinds of landslide disaster scenes with different cover area are successfully generated, including rocks rolling from hill, soil and rock collapsing, landslide flowing, and covering the road and cars. Experimental results demonstrate the potential of our method. [ABSTRACT FROM AUTHOR]

Landfills are the most popular means of disposing of construction solid waste owing to the low-cost, large treatment volume and strong adaptability. However, landfill collapses and landslides are common, posing a risk to lives and property. A catastrophic landslide, not triggered by heavy rainfall or earthquakes, occurred on December 20, 2015, at Hongao landfill in Guangming New district of Shenzhen, China. The collapsed waste soil flowed 1100 m down a slope with an elevation difference of 100 m. This catastrophic landslide is typical of long-runout disasters with high mobility, which result in great loss to life and property. In this paper, we focused on reproducing the flow processes and simulating the arriving area of the landslide at Hongao landfill using a full three-dimensional (3D) smoothed particle hydrodynamics (SPH) method. A series of undrained ring shear tests were conducted to determine the viscosity coefficient for the numerical simulation. The calculated geometry of the landslide using the full 3D SPH method agreed well with the field data. Hence, the combination of ring shear tests and SPH method can be widely used to predict the dynamic behavior of potential landslides in landfills, to reduce or prevent similar disasters. [ABSTRACT FROM AUTHOR]

This paper examines the public involvement processes contained within the Landslide Management Strategy for the District of North Vancouver in British Columbia, Canada. Following a fatal landslide in the Berkley neighborhood in 2005, the District of North Vancouver convened a community-based Natural Hazards task force to establish risk-tolerance criteria for natural hazards. This paper describes the community task force approach and evaluates it against four criteria for successful public involvement: representative participation; early involvement; information availability; and impact on policy. It is identified that the District could have incorporated a broader understanding of risk, allowing public perspectives to influence the initial framing of the risk issue before charging the Natural Hazards task force to arrive at quantitative risk-tolerance criteria. The District could also have sought to engage a somewhat more representative portion of the population to serve on the Natural Hazards task force, seeking to incorporate a broader set of public values and types of knowledge. Notwithstanding, the Natural Hazards task force successfully utilized social, legal, and scientific information for informed decision-making, and their recommended risk-tolerance criteria were enacted into policy by the District of North Vancouver as a result of the process. The paper also investigates the District's ongoing public involvement and education efforts with respect to landslide risks, considering information accessibility and its usefulness for increasing individual capacity and community resilience. Overall, the District's ongoing, dynamic approach to risk management promises to empower individuals and foster resilient communities in the aftermath of the tragic Berkley landslide. [ABSTRACT FROM AUTHOR]

Calculating the failure probability of a landslide is important in engineering related to geological process and geomorphological evolution. Strength parameters of a soil (i.e., cohesion and internal friction angle) are regarded as uncertain-but-bounded parameters. In this study, a new method is proposed for computing the landslide failure probability based on a convex set model and artificial neural network (ANN). In the new method, ANN is used to determine the limit state function of landslide stability, and the failure probability is determined using a simple iterative algorithm. The new method was applied to calculate the failure probability of the Gufenping landslide in Nanjiang, Sichuan, China. The results calculated using a Monte Carlo simulation (MCS) method confirmed that the new method accurately and quickly obtains the failure probability of a landslide. Additionally, compared with the two-dimensional calculation method, the one-dimensional analysis method overestimates the failure probability of the landslide. The results of single factor and global sensitivity analysis indicate that the average of internal friction angle is the main factor affecting the stability of the landslide. It is easy to calculate failure probability of landslides using the novel method than using the conventional methods. [ABSTRACT FROM AUTHOR]

The denudation of young reliefs prone to landslides can have severe consequences for society and the environment. However, landslide databases and the additional information (landslide type, date and triggering factors) necessary to deal with landslide hazard assessment and the development of effective and reliable landslide warning systems are usually scarce or non-existent. In this way, by taking into account the date of landslide events and by expanding the analysis of cumulative rainfall from these dates to a broader time period that includes the days or months leading up to a landslide, the corresponding triggering rainfall threshold can be assessed more accurately. In this paper, a methodology based on a partial duration series analysis applied to rainfall variables allows the possibility to better understand precipitation patterns. Another advantage of analysing precipitation variables within a broader time period is the ability to identify greater accuracy rainfall anomalies such as extreme rainfalls with their return period related to a low number of dated landslide events (in this case, 20 landslide events). The landslide spatial distribution within a regional area requires the processing and analysis of data from multiple long-term historical daily rainfall records from different rainfall gauges, which notably increase the number of calculations to be dealt with. To overcome this inconvenience, these processes were streamlined by using macro-automation. Additionally, different rainfall durations can be interactively identified from graphical outputs that show anomalies on more than one rainfall variable after applying this methodology. Among these rainfall variables, the antecedent accumulated rainfall (A1) was found to be the most suitable to apply the occurrence probability analysis. When compared to other variables, the return period values of A1 were determined to be conservative, neither too high nor too low. Using this approach, the return period curve was shown to be an important graphic object in detecting uncommon rainfalls that are contemporaneous or previous to landslides. The relevant findings of this research show a power-law trend with α = 88.005 and β = 0.69 in the correlation of intensity and duration associated with antecedent cumulative rainfall (A1) anomalies. The mean return period for these anomalies resulted in 12.4 years, while for 50 % of the landslides, the recurrence interval was estimated in less than or equal to 3.6 years. In addition, significant differences were found between catalogued slope-cut failures and natural landslides. Moreover, differences were also found between simplified types of natural landslides. [ABSTRACT FROM AUTHOR]

Intensity–duration rainfall thresholds are commonly used in regional-scale landslide warning systems. In this manuscript, 3D thresholds are defined also considering the mean rainfall amount fallen in each alert zone (MeAR, mean areal rainfall) in Emilia Romagna region (Northern Italy). In the proposed 3D approach, thresholds are represented by a plane instead of a line, and the third dimension allows to indirectly account for the influence of complex rainfall patterns. MeAR values are calculated according to different time periods ranging from 7 to 30 days, and all threshold parameters are calibrated independently for the 8 alert zones in which the region is divided. The approach was validated and compared with classical intensity–duration thresholds, finding that the 3D threshold may be used to get better performances, especially in terms of a consistent reduction of false alarms:− 20 to − 86%, depending on the alert zone and the selected MeAR duration. These results open new encouraging perspectives for the development of the regional warning system that is operated in the study area. [ABSTRACT FROM AUTHOR]

This paper deals with the formative process of the Wenchuan earthquake disaster chain risk. Selected earthquake-landslides chain risk is critically evaluated by the probability of landslide displacement failure based on the Newmark's permanent-deformation model. In this context, a conceptual model of regional disaster chain risk assessment was proposed, in which the hazard-formative environments sensitivity was the core factor as well as the main difference compared with single disaster risk assessment. The disaster chain risk is accumulation of primary disaster risk and the secondary disasters risks. Results derived from the Wenchuan case proved that the conceptual model was suitable for the disaster chain risk assessment, especially the sudden disaster chain. This experience would offer greater potential in application of conceptual model of disaster chain risk assessment, in the process of large-scale disaster risk governance. [ABSTRACT FROM AUTHOR]

Multi-platform remote sensing using space-, airborne and ground-based sensors has become essential tools for landslide assessment and disaster-risk prevention. Over the last 30 years, the multiplicity of Earth Observation satellites mission ensures uninterrupted optical and radar imagery archives. With the popularization of Unmanned Aerial Vehicles, free optical and radar imagery with high revisiting time, ground and aerial possibilities to perform high-resolution 3D point clouds and derived digital elevation models, it can make it difficult to choose the appropriate method for risk assessment. The aim of this paper is to review the mainstream remote-sensing methods commonly employed for landslide assessment, as well as processing. The purpose is to understand how remote-sensing techniques can be useful for landslide hazard detection and monitoring taking into consideration several constraints such as field location or costs of surveys. First we focus on the suitability of terrestrial, aerial and spaceborne systems that have been widely used for landslide assessment to underline their benefits and drawbacks for data acquisition, processing and interpretation. Several examples of application are presented such as Interferometry Synthetic Aperture Radar (InSAR), lasergrammetry, Terrestrial Optical Photogrammetry. Some of these techniques are unsuitable for slow moving landslides, others limited to large areas and others to local investigations. It can be complicated to select the most appropriate system. Today, the key for understanding landslides is the complementarity of methods and the automation of the data processing. All the mentioned approaches can be coupled (from field monitoring to satellite images analysis) to improve risk management, and the real challenge is to improve automatic solution for landslide recognition and monitoring for the implementation of near real-time emergency systems. [ABSTRACT FROM AUTHOR]

There is a clear need for integrated research on landslide disaster risk. Landslide disasters have major impacts in developing countries due to the increasing social vulnerability of both rural and urban communities. In recent decades, landslide disasters in Latin America triggered by both precipitation and earthquakes have also increased considerably. Thus, scientific contributions based on integrated risk research are quite urgent for improving the knowledge base for reducing the vulnerability of exposed communities to landslides. Thus, there is a parallel necessity to promote capacity building for young scientists in Latin America by considering the shift of disaster paradigm to recognize the 'unnaturalness' of disasters. Under such a framework, there are particular goals to be pursued including: (1) Development of landslide regional networks with a commitment for understanding risk as a socially constructed process; (2) Engagement of young scientists in integrated landslide risk research; (3) Inducing a scientific multi- and transdisciplinary approach for integrated landslide risk research; (4) Development and implementation of capacity building; (5) Contributing to the dissemination and application of common methodologies on landslide disasters investigations; and (6) Strengthening collaboration on integrated landslide disaster risk research in Latin America. In this paper, we present one of the main activities of the ICL Latin-American network in terms of capacity building carried out in 2013; to that end, the first international workshop on forensic investigations of disasters associated with landslides was held in the University of Sciences and Arts of Chiapas in the city of Tuxtla Gutierrez, Chiapas, Mexico, from June 26th to July 4th, 2013. [ABSTRACT FROM AUTHOR]

This paper reports experimental data on surface and deep displacements evaluated by means of GPS stations and inclinometers in two rototranslational deep landslides in a clayey slope of the Italian Southern Apennines. The displacements of the landslides cause continuous damage to buildings and infrastructures. To study these phenomena and control their effects, the local public administration provided financial support for a geotechnical investigation that started in 2004. Laboratory tests, in situ pore pressure and inclinometer measurements were carried out. In July 2006, systems of fixed-in-place inclinometer probes with continuous data acquisition were installed in two of the eleven guide casings, in correspondence to the slip surfaces detected by previous periodical measurements. In the meanwhile, a GPS network was installed, consisting in six permanent stations and ten non-permanent ones. Among the latter, five were installed on the top of five inclinometer casings. The experimental results show that, in the case under study, the surface displacements evaluated by means of the GPS stations are consistent with the surface displacements evaluated by means of the inclinometer measurements. This implies mutual data validation, availability of considerable amount of continuous data, as well as monitoring continuity when, for some reason, one of the instruments goes out of use. [ABSTRACT FROM AUTHOR]

This paper presents a short history of the appraisal of laser scanner technologies in geosciences used for imaging relief by high-resolution digital elevation models (HRDEMs) or 3D models. A general overview of light detection and ranging (LIDAR) techniques applied to landslides is given, followed by a review of different applications of LIDAR for landslide, rockfall and debris-flow. These applications are classified as: (1) Detection and characterization of mass movements; (2) Hazard assessment and susceptibility mapping; (3) Modelling; (4) Monitoring. This review emphasizes how LIDAR-derived HRDEMs can be used to investigate any type of landslides. It is clear that such HRDEMs are not yet a common tool for landslides investigations, but this technique has opened new domains of applications that still have to be developed. [ABSTRACT FROM AUTHOR]

This paper provides a detailed account of the landslide that took place between 09:00 and 10:00 am on April 25, 2009, near the village of Rampac Grande in northern Peru (department of Ancash). Lives were lost and property destroyed during the event. Archive information, remotely sensed data, and detailed field investigations including sampling were applied to describe the events. Historically, landslides have been a common problem in this region with recorded events dating as far back as the 1800s. The landslide is considered as a deep-seated composite rotational-translational earth slide-earth flow. The local community suspected that a mining company had triggered the landslide as it prospected for precious metals. No evidence was found to suggest that anthropogenic activity caused the landslide. Instead, it was likely caused by the considerable amount of cumulative precipitation during the annual rainy season. Several possible sources of future landslide reactivation have been identified. Finally, a poster has been produced for the local community providing basic information about the event and how to manage the potential future landslide hazard. It is hoped that this simple method of knowledge dissemination will provide a fundamental bridge between the efforts of research scientists and the needs of the local community. [ABSTRACT FROM AUTHOR]

Take account of the characters of road geological hazard and its supervision, it is very important to develop the Road Landslides Information Management and Forecasting System based on Geographic Information System (GIS). The paper presents the system objective, function, component modules and key techniques in the procedure of system development. The system, based on the spatial information and attribute information of road geological hazard, was developed and applied in Guizhou, a province of China where there are numerous and typical landslides. The manager of communication, using the system, can visually inquire all road landslides information based on regional road network or on the monitoring network of individual landslide. Furthermore, the system, integrated with mathematical prediction models and the GIS’s strongpoint on spatial analyzing, can assess and predict landslide developing procedure according to the field monitoring data. Thus, it can efficiently assists the road construction or management units in making decision to control the landslides and to reduce human vulnerability. [ABSTRACT FROM AUTHOR]

Little is known about the vulnerability to landslides, despite landslides causing frequent and widespread damage to the population and the built-up environment in many areas of the world. Lack of information about vulnerability to landslides limits our ability to determine landslide risk. This paper provides information on the vulnerability of buildings and roads to landslides in Umbria, central Italy. Information on 103 landslides of the slide and slide-earth flow types that have resulted in damage to buildings and roads at 90 sites in Umbria is used to establish dependencies between the area of the landslide and the vulnerability to landslides. The dependencies obtained are applied in the hills surrounding the town of Collazzone, in central Umbria, an area for which a detailed landslide inventory map is available. By exploiting the landslide inventory and the established vulnerability curves, the geographical distribution of the vulnerability to landslides is mapped and statistics of the expected damage are calculated. Reliability and limits of the vulnerability thresholds and of the obtained vulnerability assessment are discussed. [ABSTRACT FROM AUTHOR]

This paper deals with landslide hazards and risk analysis of Penang Island, Malaysia using Geographic Information System (GIS) and remote sensing data. Landslide locations in the study area were identified from interpretations of aerial photographs and field surveys. Topographical/ geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for landslide hazard analysis. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide susceptibility was analyzed using landslide-occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using the landslide location data and compared with the probabilistic model. The accuracy observed was 80.03%. The qualitative landslide hazard analysis was carried out using the frequency ratio model through the map overlay analysis in GIS environment. The accuracy of hazard map was 86.41%. Further, risk analysis was done by studying the landslide hazard map and damageable objects at risk. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network. [ABSTRACT FROM AUTHOR]

The Nepal Himalayas is one of the world's most active mountain belts and home to widespread natural hazards of various types, including landslides, which claim numerous lives and result in massive property damage in the country. Landslides occur due to the combined effects of seismic activity, monsoon rainfall, and improper land-use practices. The prevention and mitigation of landslides are challenging for countries such as Nepal. However, low-cost techniques such as bioengineering combined with affordable early warning systems have been implemented in recent decades. The Methum landslide in Lalitpur district, central Nepal, was selected as a case study to investigate the landslide geomorphology along with triggering factors and to evaluate the effectiveness of a landslide early warning system (LEWS). Multiple field visits were conducted to learn the patterns of landslide evolution, assess landslide risk, and identify potential triggers. This study analyzed aerial photos, satellite images, and precipitation records. Heavy rainfall and past earthquake events have been major landslide triggers, while sloped terrace farming has acted as a preparatory factor. LEWS, installed, measures rainfall, soil moisture, and displacement activity and generates an alarm to alert nearby inhabitants if any of these parameters exceed the threshold set. This monitoring system is a cost-effective technique and exemplifies the reduction of landslide risk at the community level in the landslide-prone mid-hills of Nepal. [ABSTRACT FROM AUTHOR]

There has been an increasing demand for detailed and accurate landslide maps and inventories in disaster-prone areas of subtropical and temperate zones, particularly in Asia as they can mitigate the impacts of landslides on social infrastructure and economic losses. Hence, in this study, models using automatically constructed high-performing convolutional neural network (CNN) architectures for landslide detection were applied and their outcomes were compared for landslide susceptibility mapping at the Kii peninsula, Japan. First, a total of 38 landslide and 63 non-landslide points were identified and divided into 70% and 30% of training and validation datasets, respectively. Eight landslide influence factors were used: slope angle, eigenvalue ratio, curvature, underground openness, overground openness, topographic witness index, wavelet, and elevation. These factors were selected using a 1-m DEM, which is easy to acquire and process data. Experimental results of model evaluation using receiver operating characteristics (ROC), area under the curve (AUC), and accuracy showed that the optimal models (ROC = 96.0%, accuracy = 88.7%) were more accurate than initial models (ROC = 91.1%, accuracy = 80.7%) in predicting landslides spatially. Furthermore, the landslide susceptibility mapping is consistent with the trends in the distribution of gentle slopes and knick lines unique to the study area and can be used as a powerful method for predicting landslides in future. [ABSTRACT FROM AUTHOR]

Some properties of landslide soils are generally recognized as inherently spatially variable because of the heterogeneity of natural geological deposits. Fluctuations in water levels of the Three Gorges Reservoir cause the depth of the groundwater table at landslide toes to change, resulting in fluctuations in the soil water content and significant soil degradation. The spatial variability and temporal weakening of soil properties should be incorporated into the landslide stability analysis. More importantly, rational deformation prediction and stability analysis of landslide numerical models require an advanced soil constitutive model. Herein, taking the Tangjiao landslide as a case study, the statistical characteristics of shear strength parameters were studied based on valuable soil test data. Then, the spatial variability of these parameters was modeled as a random field for the sliding mass. A hypoplastic constitutive model for clay was used to simulate the landslide deformation over 6 years caused by precipitation and changes in the reservoir water level. In addition, soil degradation induced by the fluctuating groundwater level was accounted for in key model parameters on the basis of experimental results. Eventually, the non-intrusive random finite element method was used to compute the landslide deformation and stability for the random field model. Landslide simulation of the deterministic model ignoring the spatial variation of soil parameters was also performed. Simulation results indicate that the difference in the landslide safety factor between the deterministic and random field models is up to 0.14 for the leading edge and up to 0.12 for the trailing edge. Random field models predict greater deformation and less stability than the deterministic model, suggesting that they are more conservative in this specific case. This research can serve as a useful reference for probabilistic stability analyses of riverside landslides considering soil spatial and temporal variability, which may be quantified more precisely in future research based on multi-source data inversion. [ABSTRACT FROM AUTHOR]

This effort is made to develop a landslide hazard map and perform the kinematic slope instability analysis of the critical sections at the Dasu dam site and its reservoir area. The study area is located at the Indus River in the Kohistan District within the highly elevated Himalayan terrain. The fragile geologic setup and high tectonic activity make this region favorable to produce frequent slope failures and landsliding events. First, a regional level landslide inventory map was created using GIS and remote-sensing tools. For this a hill shaded topographic map was created by overlapping a topographic map on to a hillshade image extracted from satellite based PALSAR Digital Elevation Model (DEM) with 12.5 m spatial resolution in GIS environment. Numerous past landsides were delineated using the expert driven knowledge of anomalous topographic expression like, crenulated contours, divergent contours, isolated topographic knobs, extended topographic ridges and arcuate headscarf evacuation areas. Total 120 landslides were marked, later a field visit was carried out for the validation of this exercise. The overall efficiency of this work was 85% which indicates that the GIS and remote sensing tools utilized for this study are reliable and effective in producing regional landslide inventory maps. Moreover, the scanline surveys were conducted at few selected locations to generate discontinuities data for the evaluation of slope instability issues by using kinematic analysis in DIPS 7.0 software. The study successfully highlights the usefulness of GIS and RS tools and in combination with kinematic analysis for landslides hazard assessment for mega projects. The outcomes of this research could serve as a guide in risk assessment and mitigation work in future to stabilize the critical slopes near Dasu dam site and along its reservoir area. [ABSTRACT FROM AUTHOR]

Landslide susceptibility maps are modelled either by knowledge-driven methods (qualitative) or data-driven methods (quantitative) depending on apriori expert knowledge or complete landslide inventory data, respectively, which hinders land regulatory authorities from taking quick decisions for land use planning at a regional scale. To overcome these limitations, a new modelling methodology is proposed which can perform equally with the existing established models and needs minimum knowledge of geo-environmental variables without any model testing data. In this method, common variances of the geo-environmental variables are extracted from initially equally weighted variables and are termed as equal weight method (EWM). The extracted common variances are used to weight the variables for the preparation of a landslide susceptibility map on a regional scale. The output of the model can be interpreted to understand the inter-relationship of different geo-environmental variables along with the identification and prioritization of variables on model performance by delineating the non-performing variables. The proposed modelling methodology is tested at the eastern Himalayan road corridor, the result of which is compared with the results of the analytical hierarchy process (qualitative) and frequency ratio (quantitative) modelling methods by area under curve (AUC) of receiver operating characteristic (ROC) curves and cost analysis. AUC of ROC curves for the analytical hierarchy process, frequency ratio method and equal weight method models are 0.755, 0.809 and 0.774, respectively, indicating little performance differences. Cost analysis of all models shows a maximum bounding cost of 0.4 indicating that all models are cost-effective. The study concludes that the equal weight method is quick, robust and cost-effective at par with other well tested knowledge-driven and data-driven methods. [ABSTRACT FROM AUTHOR]

Landslide risk analysis is a common geotechnical evaluation and it aims to protect life and infrastructure. In the case of sensitive clay zones, landslides can affect large areas and are difficult to predict. Here we propose a methodology to determine the landslide hazard across a large territory, and we apply our approach to the Saint-Jean-Vianney area, Quebec, Canada. The initial step consists of creating a 3D model of the surficial deposits of the target area. After creating a chart of the material electrical resistivity adapted for eastern Canada, we applied electric induction to interpret the regional soil. We transposed parameter values obtained from the laboratory to a larger scale, that is to a regional slope using the results of a back analysis undertaken earlier, on a smaller slide within the same area. The regional 3D model of deposits is then used to develop a zonation map of slopes that are at risk and their respective constraint areas with the study region. This approach allowed us to target specific areas where a more precise stability analysis would be required. Our methodology offers an effective tool for stability analysis in territories characterized by the presence of sensitive clays. [ABSTRACT FROM AUTHOR]

Landslides in the Himalayan region are primarily controlled by natural parameters, including rainfall, seismic activity, and anthropogenic parameters, such as the construction of large-scale projects like road development, tunneling and hydroelectric power projects and climate change. The parameters which are more crucial among these are a matter of scientific study and analysis. This research, taking Solan district, Himachal Pradesh, India, as the study area, aims to assess the impact of anthropogenic activities on landslide susceptibility at a regional scale. Landslide distribution was characterized into two groups, namely Rainfall-Induced Landslide (RIL) and Human-Induced Landslide (HIL) based on triggering factors. Multiple data such as slope angle, aspect, profile curvature, distance to drainage, distance to lineament, lithology, distance to road, normalized difference vegetation index (NDVI) and land use land cover (LULC) have been considered for delineating the landslide susceptibility zonation (LSZ) map. The effect of anthropogenic activities on landslide occurrences has been examined through the distribution of landslides along national highways and land use land cover changes (LULCC). Two sets of LSZ maps with a LULC of time interval covering five years (2017 & 2021) were prepared to compare the temporal progression of LULC and landslide susceptibility during the five years. The results indicated the significant impact of anthropogenic activities on the landslide susceptibility. LSZ map of the year 2021 shows that 23% area falls into high and very high susceptible classes and 48% area falls into very low and low susceptibility classes. Compared to LSZ map of 2017, high and very high susceptible classes have been increased by 15%, whereas very low and low susceptible classes have been reduced by 7%. The present case study will help to understand the potential driving parameters responsible for HIL and also suggest the inclusion of LULC in landslide susceptibility analysis. The study will demonstrate new opportunities for research that could help decision-makers prepare for future disasters, both in the Indian Himalayan region and other areas. [ABSTRACT FROM AUTHOR]

The 2005 Kashmir earthquake has triggered widespread landslides in the Himalayan mountains in northern Pakistan and surrounding areas, some of which are active and are still posing a significant risk. Landslides triggered by the 2005 Kashmir earthquake are extensively studied; nevertheless, spatio-temporal landslide susceptibility assessment is lacking. This can be partially attributed to the limited availability of high temporal resolution remote sensing data. We present a semi-automated technique to use the Sentinel-2 MSI data for co-seismic landslide detection, landslide activities monitoring, spatio-temporal change detection, and spatio-temporal susceptibility mapping. Time series Sentinel-2 MSI images for the period of 2016–2021 and ALOS PALSAR DEM are used for semi-automated landslide inventory map development and temporal change analysis. Spectral information combined with topographical, contextual, textural, and morphological characteristics of the landslide in Sentinel-2 images is applied for landslide detection. Subsequently, spatio-temporal landslide susceptibility maps are developed utilizing the weight of evidence statistical modeling with seven causative factors, i.e., elevation, slope, geology, aspect, distance to fault, distance to roads, and distance to streams. The results reveal that landslide occurrence increased from 2016 to 2021 and that the coverage of areas of relatively high susceptibility has increased in the study area. [ABSTRACT FROM AUTHOR]

Seismic slope stability analysis at regional scale (e.g., landslide hazard mapping, infrastructure slope management) is essential in areas that are susceptible to earthquake. Analytical infinite slope model is well suited and widely used for regional analyses which involve hundreds and thousands of slopes. Use of infinite slope model implicitly assumes shallow translational failure mechanism. However, earthquake can also cause deep rotational failure, which is more destructive and should also be considered. This study aims to develop closed-form solutions that can be efficiently used for seismic slope stability analysis at regional scale considering deep rotational failure mechanism. The existing research is critically reviewed first, and their shortcomings are identified. In contrast to the conventional "two-step" approach, a more efficient and versatile "one-step" approach is proposed in this study. The "one-step" approach can be used to calculate factor of safety for pseudo-static analysis and yield coefficient for displacement-based seismic analysis. To consider the effects of uncertainty from soil properties and seismic loading, the "one-step" approach is further extended for probabilistic analysis and application is demonstrated through a case study. The efficiency and versatility of the proposed "one-step" approach make it well suited for regional seismic slope stability analysis. [ABSTRACT FROM AUTHOR]